1. Field of the Invention
Methods and apparatuses consistent with the present invention relate to video compression, and more particularly, to increasing encoding efficiency when performing entropy encoding on a fine granular scalability layer.
2. Description of the Related Art
With the development of information communication technology including the Internet, video communication as well as text and voice communication has increased. Conventional text communication cannot satisfy users' various demands, and thus, multimedia services that can provide various types of information such as text, pictures, and music have increased. However, multimedia data requires a large-capacity storage medium and a wide bandwidth for transmission because the amount of multimedia data is usually large. Accordingly, a compression coding method is requisite for transmitting multimedia data including text, video, and audio.
A basic principle of data compression is to remove data redundancy. Data can be compressed by removing spatial redundancy in which the same color or object is repeated in an image, temporal redundancy in which there is little change between adjacent frames in a moving image or the same sound is repeated in audio, or mental visual redundancy which takes into account human eyesight and its limited perception of high frequency. In a general video coding method, the temporal redundancy is removed by temporal filtering based on motion compensation, and the spatial redundancy is removed by spatial transform.
Lossy encoding is performed on the result obtained by removing data redundancy according to predetermined quantization steps through a quantization process. Lossless encoding is finally performed on the quantized result through entropy encoding.
Currently, in the scalable video coding (SVC) standard that is being conducted by a joint video team (JVT), which is a meeting between video experts of the International Organization for Standardization/International Electro technical Commission (ISO/IEC) and the International Telecommunication Union (ITU), research on a multi-layer based scalable video coding technique based on the conventional H.264 standard has been actively made. In particular, an FGS technique is used to improve quality or bit rate of one frame.
FIG. 1 is a view illustrating the concept of a plurality of quality layers 11, 12, 13, and 14 that form one frame or slice 10 (hereinafter, referred to as “slice”). The quality layers are data that is obtained by dividing one slice and being recorded so as to support signal-to-noise ratio (SNR) scalability. An FGS layer is a representative example for the quality layer, but the invention is not limited thereto. The plurality of quality layers may include one base layer and one or more FGS layers 11, 12, and 13. Video quality measured by a video decoder becomes improved in order of when only the base layer 14 is received, when the base layer 14 and the first FGS layer 13 are received, when the base layer 14, the first FGS layer 13, and the second FGS layer 12 are received, and when all of the layers 11, 12, 13, and 14 are received.
In the SVC draft, the coding is performed using correlation between the respective FGS layers. That is, another FGS layer is coded using coefficients of one FGS layer according to separated coding passes (the concept including a significant pass and a refinement pass). At this time, when coefficients of all of the corresponding lower layers are zero, coefficients of the corresponding current layer are coded by the significant pass. When one or more coefficients of the corresponding lower layers do not have values of zero, the coefficients of the corresponding current layer are coded by the refinement pass. As such, predetermined coefficients of the FGS layers are coded by the different passes because probability distributions of the coefficients are clearly differentiated from each other according to the coefficients of the corresponding lower layers.
FIG. 2A is a graph illustrating probability of when a zero occurs with respect to corresponding coding passes when coding passes of the first FGS layer are selected by using coefficients of the discrete layer In FIG. 2A, SIG denotes a significant pass, and REF denotes a refinement pass. Referring to FIG. 2A, a probability distribution, in which a zero occurs in the coefficients of the first FGS layer that are coded by the significant pass because the corresponding coefficients of the discrete layer are zero, is clearly differentiated from a probability distribution, in which a zero occurs in the coefficients of the first FGS layer that are coded by the refinement pass because the corresponding coefficients of the discrete layer are not zero. As such, when probability distributions, in which a zero occurs, are clearly differentiated from each other, the coding efficiency can be improved by performing the coding according to the different coding passes, that is, according to different context models.
FIG. 2B is an exemplary graph illustrating probability of when a zero occurs with respect to corresponding coding passes when the coding passes of the second FGS layer are selected by using the coefficients of the discrete layer and the first FGS layer. Referring to FIG. 2B, unlike the FIG. 2A, probabilities of when a zero occurs between the coefficients of the second FGS layer, which are coded by the refinement pass, and the coefficients of the second FGS layer, which are coded by the significant pass, are not differentiated from each other, but the probabilities are mixed. That is, the coding method according to coding passes, which is disclosed in the SVC draft, is considerably efficient for the coding of the first FGS layer. However, when the coding is performed on the second FGS layer or upper layers, the efficiency may be reduced. The reduction in efficiency may be caused by the fact that probable correlation between adjacent layers is high but probable correlation between layers, which are not adjacent but slightly distant from each other, is low.